Using OpenClinica for ICF-Based Data Acquisition

The use of electronic data capture (EDC) systems in health care, and especially in clinical trials, has been the object of significant research given the potential advantages like improved data quality, reduced cost, and increased trial repeatability. Despite significant interest and promised benefits, real adoption has been somewhat limited to date with most successful implementations performed in the field of pharmaceutical clinical trials. This can be attributed in part to the lack of underlying consistent and reusable internal data models and the high cost and complexity in customizing most EDC systems.

A potential alternative to traditional EDC software is the use of Open Source Software (OSS), broadly defined as software that is distributed as a freely available and freely modifiable system. This freedom gives the user the opportunity to perform structural modifications and adaptations to better integrate the software with pre-existing IT infrastructures, or to adapt it to local needs and requirements. There are many examples of large scale open source software (OSS) systems in health care, including the VISTA electronic health record system, used in the US Department of Defense and in several hundred installations across the world, the Care2X system, Indivo health, and the OpenClinica EDC system. The use of open source software facilitates the harmonization of a coherent and comprehensive data model that can be reused across different systems. In our work, ICF (the WHO classification for functioning and disability) has been selected as the underlying representational model, and implemented in the OpenClinica EDC software. The experimentation involved more than 10 Italian regions, with multiple hospitals and care centers. The EDC system was designed to test the effectiveness of ICF as a basis for data collection on disability and functioning in a wide spectrum of pathologies.

The complete WHO-ICF classification was imported from the CLAmL XML representation into the LexGrid editor, a tool created by Mayo Clinic for the purpose of editing and maintaining ontologies and classifications. Starting from this intermediate representation, the classification was first translated into the Italian language and then exported back into the CLAmL representation; this form was also used as the basis for the creation of the internal EDC data model, later imported into the OpenClinica platform. From this visual representation, a group of experts designed the set of forms that comprise the web application; later, the database structure and the final application templates were fixed and published on a public web site. The joint use of ICF as a representational model for an Electronic Data Capture system, coupled with the choice of open source software, yielded a significant reduction in the cost and implementation time of a multiregional EDC system. The ease of use of the web interface also facilitated interactions with medical experts to quickly implement alternative data representations and to create a stable and fast platform that is currently being used in an actual trial. OpenClinica demonstrates that open source is stable and ready to be used even in the strictest clinical trials, and that by using open source it is possible to create clinical research applications in a faster and more cost effective way.